30 results about "Service placement" patented technology

An approach efficiently and dynamically places services within a multi-node system when expanding or contracting services, that is, increasing and decreasing the number of instances that host a service. Service placement decisions are made in a way that accounts for performance and availability requirements of both the service being placed and other services.

A method for service creation and mapping between at least two support systems includes provisioning a service based on a service requirement and a plurality of available data centers, collecting a value of the service requirement and a cost associated with the service, matching resource types of the data centers to resource availability, determining at least one valid data center from the plurality of data centers, and selecting a valid data center with a minimum cost for service placement and provisioning.

An approach efficiently and dynamically places services within a multi-node system when expanding or contracting services, that is, increasing and decreasing the number of instances that host a service. Service placement decisions are made in a way that accounts for performance and availability requirements of both the service being placed and other services.

Techniques to adaptively launch / replace applications and services on edge devices in a cellular infrastructure and / or adaptively place content and computation at the edge devices based on logic at the network core are provided. In one aspect, a method for dynamic placement of applications in a cellular network mobile cloud is provided which includes the steps of: (a) obtaining: (i) a model of the cellular network, (ii) a model of user mobility patterns in the cellular network, and (iii) a model of a profile of the applications; (b) upon receipt of requests from users for the applications, obtaining runtime states at edge servers in the mobile cloud; and (c) upon obtaining the runtime states at the edge servers, placing the requests among the edge servers and a core server in the mobile cloud based on the models obtained in step (a) and the runtime states obtained in step (b).

A method for service creation and mapping between at least two support systems includes provisioning a service based on a service requirement and a plurality of available data centers, collecting a value of the service requirement and a cost associated with the service, matching resource types of the data centers to resource availability, determining at least one valid data center from the plurality of data centers, and selecting a valid data center with a minimum cost for service placement and provisioning.

Several cloud observers monitor a set of clouds to collect cloud information and communicate the information to several service placement units thus forming a distributed service-placement system. The service-placement units communicate with a population of clients to receive service-assignment requests and select at least one compatible cloud for each request. The cloud observers share the cloud-monitoring workload and the service-placement units share the cloud-assignment workload. According to a first connectivity scheme, each cloud observer has a path to each service-placement unit. According to a second connectivity scheme, the cloud observers are interconnected to pool cloud information so that each cloud observer possesses cloud information of all clouds. Each cloud observer communicates with a respective subset of the service-placement units. According to a third connectivity scheme, cloud information is communicated through an intermediate stage of multicast distributors, each coupled to a respective subset of service-placement units.

The invention provides a dynamic extension and placement method and device for edge computing services, and the method comprises the steps: carrying out the dynamic extension and placement of the edge computing services according to the current respective work load intensity prediction result of each micro-service corresponding to each application in an edge computing platform and the current respective work performance evaluation result of each edge node; performing automatic expansion processing on the number of the micro-service copies according to the target data processing request so as to determine the scaling optimization number of the micro-service copies; and adopting a preset self-adaptive discrete binary particle swarm optimization algorithm to obtain a mapping relationship between each micro-service copy and each available edge node according to the scaling optimization number of the micro-service copies, the number of currently placeable edge nodes and the performance information, so as to respectively place each micro-service copy to the corresponding edge node. According to the invention, the automatic expansion reliability and effectiveness of the edge computing service can be improved under the conditions of unbalanced edge load and unreliable network state in the edge environment, and the accuracy and reliability of edge computing service placement are improved.

The invention discloses a service arrangement method for maximizing social welfare in an edge alliance, designs the horizontal cooperation of the edge alliance, and integrates all edge nodes of all EIPs. First, the present invention models the service allocation problem as a planning problem for maximizing social welfare. Then, the present invention proposes two EIP dynamic pricing methods to determine the bidding price for customers and the in-package price for other EIPs. Evaluation results based on two real datasets show that the proposed service placement model can increase the overall gain of EIP by up to 24.5%, while reducing the overall delay by 35.5%.

The embodiment of the invention provides a redundant service deployment method and device. The redundant service deployment method comprises the following steps: determining multiple to-be-deployed services contained in an application program request of a user, a resource demand of each to-be-deployed service and a communication delay demand among the to-be-deployed services, wherein each to-be-deployed service comprises a plurality of service copies; based on a preset service placement rule, allocating a physical machine node to each service copy of each service to be deployed, and screeningout a plurality of available placement decisions; calculating the reliability of the available placement decision according to the reliability of the physical machine node placed by the service copy of each to-be-deployed service and the reliability of the micro cloud; determining a final placement decision from the available placement decisions; and deploying the corresponding to-be-deployed service in the physical machine node of the micro-cloud based on the final placement decision. The resource requirement of each service of the application program, the inter-service communication requirement, the reliability of the physical machine node and the reliability factor of the micro cloud are comprehensively considered, and the high reliability of service deployment is ensured.

The invention relates to the field of information technology, and discloses a virtual service migration method and system based on incremental minimum cost and maximum flow. The method includes: constructing a network topology map according to the geographical location and connection relationship of edge servers; The shortest path distance between servers, and generate the shortest path distance matrix; combined with the access information of each service, establish the minimum cost maximum flow model, the model includes service nodes and edge server nodes; solve the model to obtain the minimum cost maximum flow, migrate and place service nodes; update the access information of each service, and use the incremental minimum cost maximum flow algorithm to update the location of service nodes; carry out real-time monitoring and statistics, when the change rate of access information exceeds When setting the threshold, adjust its corresponding service node and edge server node. The invention can solve the optimal service placement and migration scheme in a short time, and is simple, reliable and easy to implement.

The invention discloses a service placement method for maximizing social welfare in an edge alliance, designs cooperation of the edge alliance in the horizontal direction, and integrates all edge nodes of all EIPs. Firstly, a service distribution problem is modeled into a planning problem for realizing social welfare maximization; then, the invention provides two EIP dynamic pricing methods so asto determine the bid for the client and the inner package price for other EIPs. Evaluation results based on two actual data sets show that the service placement model provided by the invention can enable the total gain of the EIP to be increased by 24.5% at most, and the total delay to be reduced by 35.5%.

The invention relates to a migration method for online VMEC service network selection, which belongs to the field of mobile communication. The method includes: S1: establishing a VMEC mathematical model; S2: scanning adjacent and accessible networks at time slot t, and performing network screening; S3: repeating S2 at time slot t+1 to obtain the initial time slot t+1 Network selection and migration placement as the initial strategy; S4: Network selection and service placement optimization: calculate and compare the three delays of the initial strategy for the t+1 time slot; update the time delay of the t+1 time slot based on the comparison results of the three delays The initial strategy obtains the optimized service migration strategy Φ(t+1) for time slot t+1; finally, the access network selection and service placement are performed according to the strategy Φ(t+1); S5: In the next time slot, repeat steps S3 and S4 , get access network selection and service migration strategy for each time slot in time T. The invention can minimize the time delay for the vehicle to select the network and formulate the service migration strategy during the moving process, and improve the service quality of the user.

The invention discloses an online service placement method with data refresh based on value space estimation. In a mobile edge computing scenario, when there is service background data refresh, how to select a service for placement by an edge server is adopted to minimize the edge server The communication load with the cloud server; then the service placement problem is transformed into the shortest path problem; then the node value in the shortest path problem is estimated, and the service placement strategy for the next time slice is obtained at runtime; finally, it is achieved in the edge server Serve users and reduce the communication load between edge servers and cloud servers.

The invention discloses a user satisfaction perception-based service placement method for data centers. The method comprises the following steps: first sequencing expenditures of all the data centers at a moment t from low expenditures to high expenditures; then sequentially allocating service requests to each data center under the conditions that the center data has enough virtual machines and that the requirements of the user requests are met, reserving a group of allocation with maximum profit for a computing service provider consistent with the conditions, and placing service in the data center; and after the corresponding service is placed for all the requests, finishing the service placement of the round, and making preparations for the next moment. According to the method, the service is placed in the data centers for the user requests with minimum expenditures by taking the maximization of return of the service providers as a target on the premise of meeting satisfaction of users; and the method is easy in computation, high in operation speed and applied to online large-scale service request scenes.

A method implemented in a network for arranging services at a network device is disclosed. A network contains multiple network devices and provides a set of services to subscribers. A subset of the service set is contained in an ordered chain of services to subscribers. The method begins by determining a list of bandwidth consuming entities for each service within the service set, wherein each bandwidth consuming entity is based on one or more service chains. A weight is then calculated for each service based on the list of bandwidth consuming entities for the service, and the service with the highest weight within the group of one or more entities that have not been deployed is selected. The selected service is then placed at the network device based at least in part on calculating the bandwidth impact on the network by the service.